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Introduction to R for Quantitative Finance

You're reading from   Introduction to R for Quantitative Finance R is a statistical computing language that's ideal for answering quantitative finance questions. This book gives you both theory and practice, all in clear language with stacks of real-world examples. Ideal for R beginners or expert alike.

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Product type Paperback
Published in Nov 2013
Publisher Packt
ISBN-13 9781783280933
Length 164 pages
Edition 1st Edition
Languages
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Toc

Table of Contents (17) Chapters Close

Introduction to R for Quantitative Finance
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Preface
1. Time Series Analysis FREE CHAPTER 2. Portfolio Optimization 3. Asset Pricing Models 4. Fixed Income Securities 5. Estimating the Term Structure of Interest Rates 6. Derivatives Pricing 7. Credit Risk Management 8. Extreme Value Theory 9. Financial Networks References Index

Chapter 6. Derivatives Pricing

Derivatives are financial instruments which derive their value from (or are dependent on) the value of another product, called the underlying. The three basic types of derivatives are forward and futures contracts, swaps, and options. In this chapter we will focus on this latter class and show how basic option pricing models and some related problems can be handled in R. We will start with overviewing how to use the continuous Black-Scholes model and the binomial Cox-Ross-Rubinstein model in R, and then we will proceed with discussing the connection between these models. Furthermore, with the help of calculating and plotting of the Greeks, we will show how to analyze the most important types of market risks that options involve. Finally, we will discuss what implied volatility means and will illustrate this phenomenon by plotting the volatility smile with the help of real market data.

The most important characteristics of options compared to futures or swaps...

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